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Author Romeo Kienzler , Jerome Nilmeier
Since its 2015 release, TensorFlow has become a de facto standard among enterprise AI technologies. This comprehensive report introduces the new features of TensorFlow 2.x and Keras to developers and data scientists with machine learning skills. Many companies consider Te....
Release Date 2020/07 -
Author Mark Treveil , Lynn Heidmann
For years, organizations have struggled to move data science, machine learning, and AI projects from the realm of experimental to having real business impact. One reason is because pivoting operations around these technologies involves more than just technology--the orche....
Release Date 2020/11 -
Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification
Author Antonios Alexandridis , Achilleas Zapranis
A step-by-step introduction to modeling, training, and forecasting using wavelet networksWavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successf....
Release Date 2014/05 -
Veracity of Big Data: Machine Learning and Other Approaches to Verifying Truthfulness
Author Vishnu Pendyala
Examine the problem of maintaining the quality of big data and discover novel solutions. You will learn the four V’s of big data, including veracity, and study the problem from various angles. The solutions discussed are drawn from diverse areas of engineering and ....
Release Date 2018/06 -
Author Cristiano Bellavitis
In the venture capital (VC) industry, firms often co-invest with other peers in syndicated deals. The process of syndication is a form of investment alliance that generates networks of VC firms and start-up companies. Despite the prominent role played by syndicates....
Release Date 2017/12 -
Upgrading and Repairing Networks, Fifth Edition
Author Mark Edward Soper , Terry W Ogletree
Upgrading and Repairing Networks, Fifth Edition is the definitive guide for anyone with a network, from home networking enthusiasts to professional network administrators. The book explains network architectures and protocols using plain English and real-world exam....
Release Date 2006/05 -
Understanding support vector machines
Author Aurélien Géron
What you’ll learn—and how you can apply itYou’ll learn the core concepts one of the most popular models in Machine Learning—support vector machines—how to use them, and how they work. Readers will gain an intuitive understanding of the mathematics involved in SVMs,....
Release Date 2017/04 -
Author Natasa Kejzar , Anuska Ferligoj , Vladimir Batagelj , Patrick Doreian
This book explores social mechanisms that drive network change and link them to computationally sound models of changing structure to detect patterns. This text identifies the social processes generating these networks and how networks have evolved.
Release Date 2014/11 -
Trends in Deep Learning Methodologies
Author Vincenzo Piuri , Sandeep Raj , Angelo Genovese , Rajshree Srivastava
Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful comput....
Release Date 2020/11 -
Author Kees Wurth , Anthonie Wurth
A proven framework to fill the gap between "knowing" and "doing" Training Reinforcement offers expert guidance for more effective training outcomes. Last year, US companies spent over $165 Billion on training; while many training programs themselves provide valuabl....
Release Date 2018/07 -
Author Kim. A. Rowe
You may know that there are four distinct generations in the workplace. But while the different generations share many things, they have their own preferences for how they like to learn? Learning style preferences are driven largely by elementary school experience, ....
Release Date 2008/12 -
Author Daniel Situnayake , Pete Warden
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and ....
Release Date 2019/12 -
Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python
Author Akshay R Kulkarni , Adarsha Shivananda , Anoosh Kulkarni , V Adithya Krishnan
This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling method....
Release Date 2022/12 -
Thoughtful Machine Learning with Python
Author Matthew Kirk
Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.Featuring graphs and highlighted cod....
Release Date 2017/01 -
The Unsupervised Learning Workshop
Author Aaron Jones , Christopher Kruger , Benjamin Johnston
Learning how to apply unsupervised algorithms on unlabeled datasets from scratch can be easier than you thought with this beginner's workshop, featuring interesting examples and activitiesKey FeaturesGet familiar with the ecosystem of unsupervised algorithms Learn inter....
Release Date 2020/07 -
The Supervised Learning Workshop - Second Edition
Author Blaine Bateman , Ashish Ranjan Jha , Benjamin Johnston
Cut through the noise and get real results with a step-by-step approach to understanding supervised learning algorithmsKey FeaturesIdeal for those getting started with machine learning for the first time A step-by-step machine learning tutorial with exercises and activit....
Release Date 2020/02 -
The Reinforcement Learning Workshop
Author Alessandro Palmas , Emanuele Ghelfi , Dr. Alexandra Ga
Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guideKey FeaturesUse TensorFlow to write reinforcement learning agents for performing challe....
Release Date 2020/08 -
The Power of Product Recommendation Networks
Author Arun Sundararajan , Gal Oestreicher-Singer , Gerald C. Kane
Much as relationships in social networks have been analyzed to understand and influence how ideas flow among people, researchers wondered whether it might be possible to use the structure of product recommendation networks online to understand or influence how dema....
Release Date 2017/10 -
The Path to Predictive Analytics and Machine Learning
Author Gary Orenstein , Kevin White , Steven Camina , Conor Doherty
In many companies today, discussions about predictive analytics and machine learning tend to overlook one critical component: implementation. This report will help you examine practical methods for building and deploying scalable, production-ready machine-learning ....
Release Date 2016/10 -
The New Business Road Test, 5th Edition
Author John Mullins
ROAD TEST YOUR IDEA BEFORE YOU LAUNCH YOUR LEAN START-UP Thinking about starting a new business? Stop! Is there a genuine market for your idea? Do you really want to compete in that industry? Are you the right person to pursue it? No matter how talented you are or ....
Release Date 2017/12 -
The New Business Road Test, 4th Edition
Author John Mullins
ROAD TEST YOUR IDEA BEFORE YOU WRITE YOUR LEAN START-UP Thinking about starting a new business? Stop! Is there a genuine market for your idea? Do you really want to compete in that industry? Are you the right person to pursue it? No matter how talented you are or h....
Release Date 2013/07 -
The Machine Learning Workshop - Second Edition
Author Hyatt Saleh
Take a comprehensive and step-by-step approach to understanding machine learningKey FeaturesDiscover how to apply the scikit-learn uniform API in all types of machine learning models Understand the difference between supervised and unsupervised learning models Reinforce....
Release Date 2020/07 -
The Machine Learning Solutions Architect Handbook
Author David Ping
Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutionsKey FeaturesExplore different ML tools and frameworks to solve large-scale machine learning challenges in the cloudBuild an efficient data science environment for data explorat....
Release Date 2022/01 -
Author Konrad Banachewicz , Luca Massaron , Anthony Goldbloom
Get a step ahead of your competitors with insights from over 30 Kaggle Masters and Grandmasters. Discover tips, tricks, and best practices for competing effectively on Kaggle and becoming a better data scientist. Purchase of the print or Kindle book includes a free eBook in the PDF format.Key Fea....
Release Date 2022/04 -
Author Christian Wolmar
The Iron Road is full of wondrous curiosities. Did you know that early trains in Australia were pulled by convicts, or that elephants were until recently used to shunt freight wagons in India? The world's most magnificent railway station, the Chhatrapati Shivaji te....
Release Date 2014/05 -
The Future of Machine Intelligence
Author David Beyer
Advances in both theory and practice are throwing the promise of machine learning into sharp relief. The field has the potential to transform a range of industries, from self-driving cars to intelligent business applications. Yet machine learning is so complex and ....
Release Date 2016/03 -
The Framework for ML Governance
Most companies don't have problems building and deploying algorithmic models, but they do struggle to effectively manage them in production. Maximizing the value of machine learning projects in the enterprise requires a robust MLOps program. But there's one key challenge: The problem MLOps sets ou.... -
The Efficiency of China's Stock Market
Author Shiguang Ma
By investigating the efficiency of China's stock market in accordance with the theoretical framework of the Efficient Market Hypothesis, this book focuses on weak form and semi-strong form market efficiency. Empirical tests have been intensively conducted on the r....
Release Date 2017/11 -
Author Mirza Rahim Baig , Thomas V. Joseph , Nipun Sadvilkar
Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret textKey FeaturesUnderstand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognitio....
Release Date 2020/07